CDomainAdaptationSVMLinear Class Reference

Detailed Description

class DomainAdaptationSVMLinear

Definition at line 25 of file DomainAdaptationSVMLinear.h.

Inheritance diagram for CDomainAdaptationSVMLinear:

Public Member Functions
	CDomainAdaptationSVMLinear ()
	CDomainAdaptationSVMLinear (float64_t C, CDotFeatures *f, CLabels *lab, CLinearMachine *presvm, float64_t B)
virtual	~CDomainAdaptationSVMLinear ()
void	init (CLinearMachine *presvm, float64_t B)
virtual EClassifierType	get_classifier_type ()
virtual CLabels *	apply (CDotFeatures *data)
virtual CLinearMachine *	get_presvm ()
virtual float64_t	get_B ()
virtual float64_t	get_train_factor ()
virtual void	set_train_factor (float64_t factor)
virtual const char *	get_name () const
Public Member Functions inherited from CLibLinear
	CLibLinear ()
	CLibLinear (LIBLINEAR_SOLVER_TYPE liblinear_solver_type)
	CLibLinear (float64_t C, CDotFeatures *traindat, CLabels *trainlab)
virtual	~CLibLinear ()
LIBLINEAR_SOLVER_TYPE	get_liblinear_solver_type ()
void	set_liblinear_solver_type (LIBLINEAR_SOLVER_TYPE st)
void	set_C (float64_t c_neg, float64_t c_pos)
float64_t	get_C1 ()
float64_t	get_C2 ()
void	set_epsilon (float64_t eps)
float64_t	get_epsilon ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
int32_t	get_max_iterations ()
void	set_max_iterations (int32_t max_iter=1000)
void	set_linear_term (SGVector< float64_t > linear_term)
SGVector< float64_t >	get_linear_term ()
void	init_linear_term ()
Public Member Functions inherited from CLinearMachine
	CLinearMachine ()
virtual	~CLinearMachine ()
void	get_w (float64_t *&dst_w, int32_t &dst_dims)
SGVector< float64_t >	get_w ()
void	set_w (SGVector< float64_t > src_w)
void	set_bias (float64_t b)
float64_t	get_bias ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
virtual void	set_features (CDotFeatures *feat)
virtual CLabels *	apply ()
virtual CLabels *	apply (CFeatures *data)
virtual float64_t	apply (int32_t vec_idx)
	get output for example "vec_idx"
virtual CDotFeatures *	get_features ()
Public Member Functions inherited from CMachine
	CMachine ()
virtual	~CMachine ()
virtual bool	train (CFeatures *data=NULL)
virtual void	set_labels (CLabels *lab)
virtual CLabels *	get_labels ()
virtual float64_t	get_label (int32_t i)
void	set_max_train_time (float64_t t)
float64_t	get_max_train_time ()
void	set_solver_type (ESolverType st)
ESolverType	get_solver_type ()
virtual void	set_store_model_features (bool store_model)
Public Member Functions inherited from CSGObject
	CSGObject ()
	CSGObject (const CSGObject &orig)
virtual	~CSGObject ()
virtual bool	is_generic (EPrimitiveType *generic) const
template<class T >
void	set_generic ()
void	unset_generic ()
virtual void	print_serializable (const char *prefix="")
virtual bool	save_serializable (CSerializableFile *file, const char *prefix="")
virtual bool	load_serializable (CSerializableFile *file, const char *prefix="")
void	set_global_io (SGIO *io)
SGIO *	get_global_io ()
void	set_global_parallel (Parallel *parallel)
Parallel *	get_global_parallel ()
void	set_global_version (Version *version)
Version *	get_global_version ()
SGVector< char * >	get_modelsel_names ()
char *	get_modsel_param_descr (const char *param_name)
index_t	get_modsel_param_index (const char *param_name)

Protected Member Functions
virtual bool	is_presvm_sane ()
virtual bool	train_machine (CDotFeatures *data=NULL)
Protected Member Functions inherited from CLibLinear
virtual bool	train_machine (CFeatures *data=NULL)
Protected Member Functions inherited from CLinearMachine
virtual void	store_model_features ()

Protected Attributes
CLinearMachine *	presvm
float64_t	B
float64_t	train_factor
Protected Attributes inherited from CLibLinear
float64_t	C1
float64_t	C2
bool	use_bias
float64_t	epsilon
int32_t	max_iterations
SGVector< float64_t >	m_linear_term
LIBLINEAR_SOLVER_TYPE	liblinear_solver_type
Protected Attributes inherited from CLinearMachine
int32_t	w_dim
float64_t *	w
float64_t	bias
CDotFeatures *	features
Protected Attributes inherited from CMachine
float64_t	max_train_time
CLabels *	labels
ESolverType	solver_type
bool	m_store_model_features

Additional Inherited Members
Public Attributes inherited from CSGObject
SGIO *	io
Parallel *	parallel
Version *	version
Parameter *	m_parameters
Parameter *	m_model_selection_parameters

Constructor & Destructor Documentation

CDomainAdaptationSVMLinear

(

)

default constructor

Definition at line 24 of file DomainAdaptationSVMLinear.cpp.

CDomainAdaptationSVMLinear	(	float64_t	C,
		CDotFeatures *	f,
		CLabels *	lab,
		CLinearMachine *	presvm,
		float64_t	B
	)

constructor

Parameters

C	cost constant C
f	features
lab	labels
presvm	trained SVM to regularize against
B	trade-off constant B

Definition at line 30 of file DomainAdaptationSVMLinear.cpp.

~CDomainAdaptationSVMLinear ( )

virtual

destructor

Definition at line 37 of file DomainAdaptationSVMLinear.cpp.

Member Function Documentation

CLabels * apply ( CDotFeatures *  data )

virtual

classify objects

Parameters

data	(test)data to be classified

Returns

classified labels

Definition at line 200 of file DomainAdaptationSVMLinear.cpp.

float64_t get_B ( )

virtual

getter for regularization parameter B

Returns

regularization parameter B

Definition at line 182 of file DomainAdaptationSVMLinear.cpp.

virtual EClassifierType get_classifier_type ( )

virtual

get classifier type

Returns

classifier type DASVMLINEAR

Reimplemented from CLibLinear.

Definition at line 60 of file DomainAdaptationSVMLinear.h.

virtual const char* get_name ( ) const

virtual

get linear term

Returns

lin the linear term

object name

Reimplemented from CLibLinear.

Definition at line 114 of file DomainAdaptationSVMLinear.h.

CLinearMachine * get_presvm ( )

virtual

returns SVM that is used as prior information

Returns

presvm

Definition at line 176 of file DomainAdaptationSVMLinear.cpp.

float64_t get_train_factor ( )

virtual

getter for train_factor

Returns

train_factor

Definition at line 188 of file DomainAdaptationSVMLinear.cpp.

void init	(	CLinearMachine *	presvm,
		float64_t	B
	)

init SVM

Parameters

presvm	trained SVM to regularize against
B	trade-off constant B

Definition at line 45 of file DomainAdaptationSVMLinear.cpp.

bool is_presvm_sane ( )

protectedvirtual

check sanity of presvm

Returns

true if sane, throws SG_ERROR otherwise

Definition at line 74 of file DomainAdaptationSVMLinear.cpp.

void set_train_factor ( float64_t  factor )

virtual

setter for train_factor

Definition at line 194 of file DomainAdaptationSVMLinear.cpp.

bool train_machine ( CDotFeatures *  data = NULL )

protectedvirtual

train SVM classifier

Parameters

data	training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data)

Returns

whether training was successful

Definition at line 97 of file DomainAdaptationSVMLinear.cpp.

Member Data Documentation

float64_t B

protected

regularization parameter B

Definition at line 141 of file DomainAdaptationSVMLinear.h.

CLinearMachine* presvm

protected

SVM to regularize against

Definition at line 137 of file DomainAdaptationSVMLinear.h.

float64_t train_factor

protected

flag to switch off regularization in training

Definition at line 145 of file DomainAdaptationSVMLinear.h.

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The documentation for this class was generated from the following files:

• DomainAdaptationSVMLinear.h
• DomainAdaptationSVMLinear.cpp